{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/Christina/Dropbox/Work/Projects/2011/Weak States/analysis/replication package/WeakStates.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 7 Mar 2011, 09:28:10
{txt}
{com}. ***********
> **Graphs***;
. ***********
> 
> #delimit ;
. twoway (line ctot_pct year, sort) if country=="Greece"&year>1980,       xtitle("") ytitle("Budget Receipts (%)") legend(off) 
>         scheme(s1mono) xlabel(1981(5)2006);
{res}{txt}
{com}. graph export "receipts_Greece.eps", replace;
{txt}(note: file receipts_Greece.eps not found)
(file receipts_Greece.eps written in EPS format)

{com}. twoway (line ctotnet year, sort) if country=="Greece"&year>1980, xtitle("") ytitle("Budget Receipts (Net)") 
>         legend(off) scheme(s1mono) xlabel(1981(5)2006);
{res}{txt}
{com}. graph export "netreceipts_Greece.eps", replace;
{txt}(note: file netreceipts_Greece.eps not found)
(file netreceipts_Greece.eps written in EPS format)

{com}. ***********
> **Table 1**;
. ***********
> 
> #delimit ;
. * FE Models with panel-corrected standard errors and panel-specific ar(1) process;
. xtpcse ctot_pct conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion  employ_agriculture_ln sscouncil_pct 
>         eusupport newmember  size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 3,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.08; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      402
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.08
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.8691
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}30{txt}){col 68}= {res} 7.06e+06
{txt}Estimated coefficients{col 28}= {res}       37{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}    ctot_pct{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} .4739838{col 26}{space 2} .0968051{col 37}{space 1}    4.90{col 46}{space 3}0.000{col 54}{space 4} .2842492{col 67}{space 3} .6637184
{txt}extraordin~y {c |}{col 14}{res}{space 2} .2884917{col 26}{space 2} .0900238{col 37}{space 1}    3.20{col 46}{space 3}0.001{col 54}{space 4} .1120482{col 67}{space 3} .4649352
{txt}conflict_new {c |}{col 14}{res}{space 2}-2.803984{col 26}{space 2} .5281526{col 37}{space 1}   -5.31{col 46}{space 3}0.000{col 54}{space 4}-3.839144{col 67}{space 3}-1.768824
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2}-.2468933{col 26}{space 2} .0668185{col 37}{space 1}   -3.69{col 46}{space 3}0.000{col 54}{space 4}-.3778551{col 67}{space 3}-.1159316
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} .0301708{col 26}{space 2} .0050114{col 37}{space 1}    6.02{col 46}{space 3}0.000{col 54}{space 4} .0203487{col 67}{space 3} .0399929
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2}-.1640808{col 26}{space 2} .2586469{col 37}{space 1}   -0.63{col 46}{space 3}0.526{col 54}{space 4}-.6710194{col 67}{space 3} .3428578
{txt}employ_agr~n {c |}{col 14}{res}{space 2}  .513185{col 26}{space 2} .3047308{col 37}{space 1}    1.68{col 46}{space 3}0.092{col 54}{space 4}-.0840765{col 67}{space 3} 1.110446
{txt}sscouncil_~t {c |}{col 14}{res}{space 2} .4967503{col 26}{space 2} .0486725{col 37}{space 1}   10.21{col 46}{space 3}0.000{col 54}{space 4}  .401354{col 67}{space 3} .5921467
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2}-.0095727{col 26}{space 2} .0034743{col 37}{space 1}   -2.76{col 46}{space 3}0.006{col 54}{space 4}-.0163822{col 67}{space 3}-.0027632
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-.4325088{col 26}{space 2} .1343541{col 37}{space 1}   -3.22{col 46}{space 3}0.001{col 54}{space 4} -.695838{col 67}{space 3}-.1691795
{txt}{space 8}size {c |}{col 14}{res}{space 2}-.0617402{col 26}{space 2} .0258871{col 37}{space 1}   -2.38{col 46}{space 3}0.017{col 54}{space 4} -.112478{col 67}{space 3}-.0110025
{txt}population~n {c |}{col 14}{res}{space 2}-11.08797{col 26}{space 2} 2.447012{col 37}{space 1}   -4.53{col 46}{space 3}0.000{col 54}{space 4}-15.88402{col 67}{space 3} -6.29191
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2}-7.721335{col 26}{space 2} 1.599846{col 37}{space 1}   -4.83{col 46}{space 3}0.000{col 54}{space 4}-10.85698{col 67}{space 3}-4.585693
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2} 27.23158{col 26}{space 2} 5.484263{col 37}{space 1}    4.97{col 46}{space 3}0.000{col 54}{space 4} 16.48262{col 67}{space 3} 37.98054
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 4.390258{col 26}{space 2} .7728112{col 37}{space 1}    5.68{col 46}{space 3}0.000{col 54}{space 4} 2.875576{col 67}{space 3}  5.90494
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 23.72112{col 26}{space 2} 3.681139{col 37}{space 1}    6.44{col 46}{space 3}0.000{col 54}{space 4} 16.50622{col 67}{space 3} 30.93602
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2} 25.82291{col 26}{space 2} 4.664204{col 37}{space 1}    5.54{col 46}{space 3}0.000{col 54}{space 4} 16.68123{col 67}{space 3} 34.96458
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2}-9.072732{col 26}{space 2} 2.540414{col 37}{space 1}   -3.57{col 46}{space 3}0.000{col 54}{space 4}-14.05185{col 67}{space 3}-4.093612
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2} 23.37941{col 26}{space 2} 4.653615{col 37}{space 1}    5.02{col 46}{space 3}0.000{col 54}{space 4}  14.2585{col 67}{space 3} 32.50033
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2}-36.90851{col 26}{space 2} 8.198712{col 37}{space 1}   -4.50{col 46}{space 3}0.000{col 54}{space 4} -52.9777{col 67}{space 3}-20.83933
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2} 6.539375{col 26}{space 2} 1.258963{col 37}{space 1}    5.19{col 46}{space 3}0.000{col 54}{space 4} 4.071852{col 67}{space 3} 9.006897
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2}-3.517509{col 26}{space 2} .6686022{col 37}{space 1}   -5.26{col 46}{space 3}0.000{col 54}{space 4}-4.827945{col 67}{space 3}-2.207073
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2} 3.325509{col 26}{space 2} .7929376{col 37}{space 1}    4.19{col 46}{space 3}0.000{col 54}{space 4}  1.77138{col 67}{space 3} 4.879638
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2}-7.739674{col 26}{space 2} 1.666743{col 37}{space 1}   -4.64{col 46}{space 3}0.000{col 54}{space 4}-11.00643{col 67}{space 3}-4.472918
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2} -2.56555{col 26}{space 2}  .482157{col 37}{space 1}   -5.32{col 46}{space 3}0.000{col 54}{space 4}-3.510561{col 67}{space 3} -1.62054
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2} 20.64427{col 26}{space 2} 4.562105{col 37}{space 1}    4.53{col 46}{space 3}0.000{col 54}{space 4} 11.70271{col 67}{space 3} 29.58583
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2} -23.8053{col 26}{space 2} 6.722906{col 37}{space 1}   -3.54{col 46}{space 3}0.000{col 54}{space 4}-36.98196{col 67}{space 3}-10.62865
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2}-28.69995{col 26}{space 2} 8.519596{col 37}{space 1}   -3.37{col 46}{space 3}0.001{col 54}{space 4}-45.39805{col 67}{space 3}-12.00184
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 4.899374{col 26}{space 2} .7932164{col 37}{space 1}    6.18{col 46}{space 3}0.000{col 54}{space 4} 3.344698{col 67}{space 3} 6.454049
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 4.339358{col 26}{space 2}  1.41567{col 37}{space 1}    3.07{col 46}{space 3}0.002{col 54}{space 4} 1.564697{col 67}{space 3}  7.11402
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2}-12.78526{col 26}{space 2} 4.207547{col 37}{space 1}   -3.04{col 46}{space 3}0.002{col 54}{space 4} -21.0319{col 67}{space 3}-4.538621
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2} -1.13463{col 26}{space 2} 1.918184{col 37}{space 1}   -0.59{col 46}{space 3}0.554{col 54}{space 4}-4.894201{col 67}{space 3} 2.624942
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 5.054744{col 26}{space 2} .8288358{col 37}{space 1}    6.10{col 46}{space 3}0.000{col 54}{space 4} 3.430255{col 67}{space 3} 6.679232
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2}-15.99973{col 26}{space 2} 5.317943{col 37}{space 1}   -3.01{col 46}{space 3}0.003{col 54}{space 4}-26.42271{col 67}{space 3}-5.576754
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2}-10.40837{col 26}{space 2} 3.901712{col 37}{space 1}   -2.67{col 46}{space 3}0.008{col 54}{space 4}-18.05559{col 67}{space 3}-2.761159
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2}-6.275718{col 26}{space 2} 2.914904{col 37}{space 1}   -2.15{col 46}{space 3}0.031{col 54}{space 4}-11.98882{col 67}{space 3}-.5626122
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 178.1034{col 26}{space 2} 39.29614{col 37}{space 1}    4.53{col 46}{space 3}0.000{col 54}{space 4} 101.0843{col 67}{space 3} 255.1224
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .5179967{txt} {res} .6817705{txt} {res} .6283309{txt} {res} .6405674{txt} {res} .5726498{txt} ... {res} .4862152
{txt}{hline 78}

{com}. xtpcse ctotnet conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion  employ_agriculture_ln sscouncil_pct 
>         eusupport   newmember size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 2,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.04; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      401
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.04
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.6920
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}28{txt}){col 68}= {res} 9.12e+06
{txt}Estimated coefficients{col 28}= {res}       37{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}     ctotnet{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} 484.1697{col 26}{space 2} 161.6551{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} 167.3315{col 67}{space 3} 801.0078
{txt}extraordin~y {c |}{col 14}{res}{space 2} 458.5961{col 26}{space 2} 142.0397{col 37}{space 1}    3.23{col 46}{space 3}0.001{col 54}{space 4} 180.2033{col 67}{space 3} 736.9889
{txt}conflict_new {c |}{col 14}{res}{space 2}-2560.967{col 26}{space 2} 584.3981{col 37}{space 1}   -4.38{col 46}{space 3}0.000{col 54}{space 4}-3706.366{col 67}{space 3}-1415.568
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2}-78.10652{col 26}{space 2} 71.38671{col 37}{space 1}   -1.09{col 46}{space 3}0.274{col 54}{space 4}-218.0219{col 67}{space 3} 61.80887
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} 3.069227{col 26}{space 2} 4.450367{col 37}{space 1}    0.69{col 46}{space 3}0.490{col 54}{space 4}-5.653332{col 67}{space 3} 11.79179
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2}  343.522{col 26}{space 2} 285.8971{col 37}{space 1}    1.20{col 46}{space 3}0.230{col 54}{space 4} -216.826{col 67}{space 3}   903.87
{txt}employ_agr~n {c |}{col 14}{res}{space 2}-34.23674{col 26}{space 2} 295.7744{col 37}{space 1}   -0.12{col 46}{space 3}0.908{col 54}{space 4}-613.9438{col 67}{space 3} 545.4703
{txt}sscouncil_~t {c |}{col 14}{res}{space 2} 406.1987{col 26}{space 2} 51.28721{col 37}{space 1}    7.92{col 46}{space 3}0.000{col 54}{space 4} 305.6776{col 67}{space 3} 506.7198
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2} 10.20346{col 26}{space 2} 2.900102{col 37}{space 1}    3.52{col 46}{space 3}0.000{col 54}{space 4} 4.519363{col 67}{space 3} 15.88756
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-502.0456{col 26}{space 2}  151.934{col 37}{space 1}   -3.30{col 46}{space 3}0.001{col 54}{space 4}-799.8307{col 67}{space 3}-204.2605
{txt}{space 8}size {c |}{col 14}{res}{space 2}-13.94154{col 26}{space 2} 24.13448{col 37}{space 1}   -0.58{col 46}{space 3}0.563{col 54}{space 4}-61.24426{col 67}{space 3} 33.36117
{txt}population~n {c |}{col 14}{res}{space 2} -1367.53{col 26}{space 2}  2264.71{col 37}{space 1}   -0.60{col 46}{space 3}0.546{col 54}{space 4} -5806.28{col 67}{space 3}  3071.22
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2} 1619.376{col 26}{space 2} 1590.006{col 37}{space 1}    1.02{col 46}{space 3}0.308{col 54}{space 4}-1496.978{col 67}{space 3} 4735.731
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2}-7946.872{col 26}{space 2} 5177.085{col 37}{space 1}   -1.54{col 46}{space 3}0.125{col 54}{space 4}-18093.77{col 67}{space 3} 2200.028
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 5196.999{col 26}{space 2} 804.7106{col 37}{space 1}    6.46{col 46}{space 3}0.000{col 54}{space 4} 3619.795{col 67}{space 3} 6774.203
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 7170.352{col 26}{space 2} 3738.158{col 37}{space 1}    1.92{col 46}{space 3}0.055{col 54}{space 4}-156.3027{col 67}{space 3} 14497.01
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2} -1430.88{col 26}{space 2} 4487.971{col 37}{space 1}   -0.32{col 46}{space 3}0.750{col 54}{space 4}-10227.14{col 67}{space 3} 7365.382
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2} 2268.008{col 26}{space 2} 2269.314{col 37}{space 1}    1.00{col 46}{space 3}0.318{col 54}{space 4}-2179.766{col 67}{space 3} 6715.782
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2}-650.4565{col 26}{space 2} 4596.345{col 37}{space 1}   -0.14{col 46}{space 3}0.887{col 54}{space 4}-9659.127{col 67}{space 3} 8358.214
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2}-2215.524{col 26}{space 2} 8072.399{col 37}{space 1}   -0.27{col 46}{space 3}0.784{col 54}{space 4}-18037.14{col 67}{space 3} 13606.09
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2}-104.7018{col 26}{space 2} 1327.167{col 37}{space 1}   -0.08{col 46}{space 3}0.937{col 54}{space 4}-2705.901{col 67}{space 3} 2496.498
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2} 1515.969{col 26}{space 2} 491.8202{col 37}{space 1}    3.08{col 46}{space 3}0.002{col 54}{space 4} 552.0187{col 67}{space 3} 2479.918
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2} 4615.595{col 26}{space 2} 950.5295{col 37}{space 1}    4.86{col 46}{space 3}0.000{col 54}{space 4} 2752.591{col 67}{space 3} 6478.598
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2} 1948.225{col 26}{space 2} 1498.186{col 37}{space 1}    1.30{col 46}{space 3}0.193{col 54}{space 4}-988.1653{col 67}{space 3} 4884.616
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2} 1165.175{col 26}{space 2} 404.0031{col 37}{space 1}    2.88{col 46}{space 3}0.004{col 54}{space 4} 373.3432{col 67}{space 3} 1957.006
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2}-2594.752{col 26}{space 2} 4346.245{col 37}{space 1}   -0.60{col 46}{space 3}0.551{col 54}{space 4}-11113.24{col 67}{space 3} 5923.732
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2}  3044.24{col 26}{space 2} 6141.478{col 37}{space 1}    0.50{col 46}{space 3}0.620{col 54}{space 4}-8992.836{col 67}{space 3} 15081.32
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2} 1994.393{col 26}{space 2} 7884.065{col 37}{space 1}    0.25{col 46}{space 3}0.800{col 54}{space 4}-13458.09{col 67}{space 3} 17446.88
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 5543.093{col 26}{space 2} 866.0352{col 37}{space 1}    6.40{col 46}{space 3}0.000{col 54}{space 4} 3845.695{col 67}{space 3} 7240.491
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 5322.769{col 26}{space 2} 1374.775{col 37}{space 1}    3.87{col 46}{space 3}0.000{col 54}{space 4}  2628.26{col 67}{space 3} 8017.279
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2} 4076.193{col 26}{space 2} 3697.703{col 37}{space 1}    1.10{col 46}{space 3}0.270{col 54}{space 4}-3171.172{col 67}{space 3} 11323.56
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2} 5230.789{col 26}{space 2} 1490.193{col 37}{space 1}    3.51{col 46}{space 3}0.000{col 54}{space 4} 2310.064{col 67}{space 3} 8151.513
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 6025.642{col 26}{space 2} 870.2346{col 37}{space 1}    6.92{col 46}{space 3}0.000{col 54}{space 4} 4320.013{col 67}{space 3}  7731.27
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2} 3687.307{col 26}{space 2} 4730.435{col 37}{space 1}    0.78{col 46}{space 3}0.436{col 54}{space 4}-5584.175{col 67}{space 3} 12958.79
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2} 4689.138{col 26}{space 2} 3256.868{col 37}{space 1}    1.44{col 46}{space 3}0.150{col 54}{space 4}-1694.206{col 67}{space 3} 11072.48
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2} 4874.827{col 26}{space 2} 2295.523{col 37}{space 1}    2.12{col 46}{space 3}0.034{col 54}{space 4} 375.6841{col 67}{space 3}  9373.97
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 17798.33{col 26}{space 2} 35965.29{col 37}{space 1}    0.49{col 46}{space 3}0.621{col 54}{space 4}-52692.34{col 67}{space 3}    88289
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .6184093{txt} {res} .7922519{txt} {res} .7372506{txt} {res} .7167136{txt} {res} .5818257{txt} ... {res} .4375561
{txt}{hline 78}

{com}. ***********
> **Table 2**;
. ***********
> 
> #delimit ;
. xtpcse ctot_pct conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion  employ_agriculture_ln sscouncil_pct ssconflict
>         eusupport newmember  size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 3,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.08; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      402
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.08
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.8701
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}31{txt}){col 68}= {res} 4.21e+06
{txt}Estimated coefficients{col 28}= {res}       38{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}    ctot_pct{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} .4912631{col 26}{space 2} .1981575{col 37}{space 1}    2.48{col 46}{space 3}0.013{col 54}{space 4} .1028817{col 67}{space 3} .8796446
{txt}extraordin~y {c |}{col 14}{res}{space 2} .2940774{col 26}{space 2} .0879411{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4}  .121716{col 67}{space 3} .4664387
{txt}conflict_new {c |}{col 14}{res}{space 2}-2.808211{col 26}{space 2}    .5303{col 37}{space 1}   -5.30{col 46}{space 3}0.000{col 54}{space 4} -3.84758{col 67}{space 3}-1.768842
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2}-.2466393{col 26}{space 2} .0672791{col 37}{space 1}   -3.67{col 46}{space 3}0.000{col 54}{space 4}-.3785039{col 67}{space 3}-.1147746
{txt}gdpperca~100 {c |}{col 14}{res}{space 2}  .030208{col 26}{space 2} .0050492{col 37}{space 1}    5.98{col 46}{space 3}0.000{col 54}{space 4} .0203117{col 67}{space 3} .0401044
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2}-.1683984{col 26}{space 2} .2608339{col 37}{space 1}   -0.65{col 46}{space 3}0.519{col 54}{space 4}-.6796236{col 67}{space 3} .3428267
{txt}employ_agr~n {c |}{col 14}{res}{space 2} .5179877{col 26}{space 2} .3060453{col 37}{space 1}    1.69{col 46}{space 3}0.091{col 54}{space 4}  -.08185{col 67}{space 3} 1.117825
{txt}sscouncil_~t {c |}{col 14}{res}{space 2}  .496457{col 26}{space 2} .0478976{col 37}{space 1}   10.36{col 46}{space 3}0.000{col 54}{space 4} .4025795{col 67}{space 3} .5903346
{txt}{space 2}ssconflict {c |}{col 14}{res}{space 2}-.0016068{col 26}{space 2} .0215001{col 37}{space 1}   -0.07{col 46}{space 3}0.940{col 54}{space 4}-.0437462{col 67}{space 3} .0405325
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2}-.0095671{col 26}{space 2} .0035434{col 37}{space 1}   -2.70{col 46}{space 3}0.007{col 54}{space 4}-.0165121{col 67}{space 3}-.0026222
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-.4301467{col 26}{space 2} .1375198{col 37}{space 1}   -3.13{col 46}{space 3}0.002{col 54}{space 4}-.6996805{col 67}{space 3}-.1606129
{txt}{space 8}size {c |}{col 14}{res}{space 2}-.0627353{col 26}{space 2} .0262973{col 37}{space 1}   -2.39{col 46}{space 3}0.017{col 54}{space 4}-.1142771{col 67}{space 3}-.0111935
{txt}population~n {c |}{col 14}{res}{space 2}-10.99393{col 26}{space 2} 2.506326{col 37}{space 1}   -4.39{col 46}{space 3}0.000{col 54}{space 4}-15.90624{col 67}{space 3}-6.081626
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2}-7.661558{col 26}{space 2} 1.635399{col 37}{space 1}   -4.68{col 46}{space 3}0.000{col 54}{space 4}-10.86688{col 67}{space 3}-4.456235
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2} 27.02678{col 26}{space 2} 5.601241{col 37}{space 1}    4.83{col 46}{space 3}0.000{col 54}{space 4} 16.04855{col 67}{space 3} 38.00501
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 4.386516{col 26}{space 2} .7752059{col 37}{space 1}    5.66{col 46}{space 3}0.000{col 54}{space 4}  2.86714{col 67}{space 3} 5.905891
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 23.58893{col 26}{space 2} 3.757289{col 37}{space 1}    6.28{col 46}{space 3}0.000{col 54}{space 4} 16.22478{col 67}{space 3} 30.95308
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2} 25.65091{col 26}{space 2} 4.760398{col 37}{space 1}    5.39{col 46}{space 3}0.000{col 54}{space 4} 16.32071{col 67}{space 3} 34.98112
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2}-8.977426{col 26}{space 2} 2.603324{col 37}{space 1}   -3.45{col 46}{space 3}0.001{col 54}{space 4}-14.07985{col 67}{space 3}-3.875005
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2} 23.20919{col 26}{space 2} 4.747342{col 37}{space 1}    4.89{col 46}{space 3}0.000{col 54}{space 4} 13.90457{col 67}{space 3}  32.5138
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2}-36.59539{col 26}{space 2} 8.389609{col 37}{space 1}   -4.36{col 46}{space 3}0.000{col 54}{space 4}-53.03872{col 67}{space 3}-20.15206
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2} 6.497716{col 26}{space 2} 1.276394{col 37}{space 1}    5.09{col 46}{space 3}0.000{col 54}{space 4}  3.99603{col 67}{space 3} 8.999402
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2}-3.504115{col 26}{space 2} .6851922{col 37}{space 1}   -5.11{col 46}{space 3}0.000{col 54}{space 4}-4.847067{col 67}{space 3}-2.161163
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2}  3.32517{col 26}{space 2} .7938295{col 37}{space 1}    4.19{col 46}{space 3}0.000{col 54}{space 4} 1.769293{col 67}{space 3} 4.881048
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2}-7.675867{col 26}{space 2} 1.709054{col 37}{space 1}   -4.49{col 46}{space 3}0.000{col 54}{space 4}-11.02555{col 67}{space 3}-4.326183
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2}-2.553269{col 26}{space 2} .4920055{col 37}{space 1}   -5.19{col 46}{space 3}0.000{col 54}{space 4}-3.517582{col 67}{space 3}-1.588956
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2} 20.47644{col 26}{space 2} 4.665075{col 37}{space 1}    4.39{col 46}{space 3}0.000{col 54}{space 4} 11.33306{col 67}{space 3} 29.61981
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2} -23.5378{col 26}{space 2} 6.874532{col 37}{space 1}   -3.42{col 46}{space 3}0.001{col 54}{space 4}-37.01164{col 67}{space 3}-10.06396
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2}-28.36058{col 26}{space 2} 8.710268{col 37}{space 1}   -3.26{col 46}{space 3}0.001{col 54}{space 4} -45.4324{col 67}{space 3}-11.28877
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 4.915302{col 26}{space 2} .7919337{col 37}{space 1}    6.21{col 46}{space 3}0.000{col 54}{space 4} 3.363141{col 67}{space 3} 6.467464
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 4.345497{col 26}{space 2} 1.414545{col 37}{space 1}    3.07{col 46}{space 3}0.002{col 54}{space 4}  1.57304{col 67}{space 3} 7.117954
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2}-12.61341{col 26}{space 2} 4.307137{col 37}{space 1}   -2.93{col 46}{space 3}0.003{col 54}{space 4}-21.05525{col 67}{space 3}-4.171577
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2}-1.055279{col 26}{space 2} 1.957517{col 37}{space 1}   -0.54{col 46}{space 3}0.590{col 54}{space 4}-4.891941{col 67}{space 3} 2.781382
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 5.072243{col 26}{space 2}  .827648{col 37}{space 1}    6.13{col 46}{space 3}0.000{col 54}{space 4} 3.450083{col 67}{space 3} 6.694404
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2}-15.78483{col 26}{space 2} 5.439034{col 37}{space 1}   -2.90{col 46}{space 3}0.004{col 54}{space 4}-26.44514{col 67}{space 3}-5.124514
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2} -10.2501{col 26}{space 2} 3.989326{col 37}{space 1}   -2.57{col 46}{space 3}0.010{col 54}{space 4}-18.06903{col 67}{space 3} -2.43116
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2}-6.156907{col 26}{space 2} 2.982363{col 37}{space 1}   -2.06{col 46}{space 3}0.039{col 54}{space 4}-12.00223{col 67}{space 3}-.3115826
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 176.6075{col 26}{space 2} 40.22837{col 37}{space 1}    4.39{col 46}{space 3}0.000{col 54}{space 4} 97.76139{col 67}{space 3} 255.4537
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .5140558{txt} {res}  .683284{txt} {res} .6284833{txt} {res} .6385512{txt} {res} .5725141{txt} ... {res} .4850061
{txt}{hline 78}

{com}. *10 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(2);

Condition: sscouncil_pct=2
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .4880495{col 24}  .161653{col 38} 3.019{col 47}0.003{col 58} .1712155{col 70} .8048836
------------------------------------------------------------------------------
{txt}
{com}. *25 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(3.5);

Condition: sscouncil_pct=3.5
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .4856393{col 24} .1367754{col 38} 3.551{col 47}0.000{col 58} .2175645{col 70} .7537141
------------------------------------------------------------------------------
{txt}
{com}. *50 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(5.7);

Condition: sscouncil_pct=5.7
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .4821043{col 24}  .107617{col 38} 4.480{col 47}0.000{col 58} .2711788{col 70} .6930299
------------------------------------------------------------------------------
{txt}
{com}. *75 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(11.7);

Condition: sscouncil_pct=11.7
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .4724635{col 24} .1220226{col 38} 3.872{col 47}0.000{col 58} .2333036{col 70} .7116234
------------------------------------------------------------------------------
{txt}
{com}. *90 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(13.4);

Condition: sscouncil_pct=13.4
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .4697319{col 24} .1479111{col 38} 3.176{col 47}0.001{col 58} .1798315{col 70} .7596324
------------------------------------------------------------------------------
{txt}
{com}. xtpcse ctotnet conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion  employ_agriculture_ln sscouncil_pct  ssconflict
>         eusupport   newmember size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 2,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.04; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      401
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.04
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.6951
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}29{txt}){col 68}= {res} 1.04e+07
{txt}Estimated coefficients{col 28}= {res}       38{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}     ctotnet{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} 508.7583{col 26}{space 2} 209.8017{col 37}{space 1}    2.42{col 46}{space 3}0.015{col 54}{space 4} 97.55448{col 67}{space 3} 919.9622
{txt}extraordin~y {c |}{col 14}{res}{space 2} 472.0782{col 26}{space 2} 142.7086{col 37}{space 1}    3.31{col 46}{space 3}0.001{col 54}{space 4} 192.3745{col 67}{space 3} 751.7818
{txt}conflict_new {c |}{col 14}{res}{space 2}-2560.789{col 26}{space 2} 587.5397{col 37}{space 1}   -4.36{col 46}{space 3}0.000{col 54}{space 4}-3712.346{col 67}{space 3}-1409.233
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2} -81.8543{col 26}{space 2} 72.27747{col 37}{space 1}   -1.13{col 46}{space 3}0.257{col 54}{space 4}-223.5155{col 67}{space 3} 59.80694
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} 3.003271{col 26}{space 2} 4.484119{col 37}{space 1}    0.67{col 46}{space 3}0.503{col 54}{space 4} -5.78544{col 67}{space 3} 11.79198
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2} 339.3043{col 26}{space 2} 287.8475{col 37}{space 1}    1.18{col 46}{space 3}0.238{col 54}{space 4}-224.8665{col 67}{space 3} 903.4751
{txt}employ_agr~n {c |}{col 14}{res}{space 2}-29.14139{col 26}{space 2} 297.0345{col 37}{space 1}   -0.10{col 46}{space 3}0.922{col 54}{space 4}-611.3183{col 67}{space 3} 553.0355
{txt}sscouncil_~t {c |}{col 14}{res}{space 2} 406.0584{col 26}{space 2}  50.0552{col 37}{space 1}    8.11{col 46}{space 3}0.000{col 54}{space 4}  307.952{col 67}{space 3} 504.1648
{txt}{space 2}ssconflict {c |}{col 14}{res}{space 2}-1.813957{col 26}{space 2} 20.61028{col 37}{space 1}   -0.09{col 46}{space 3}0.930{col 54}{space 4}-42.20935{col 67}{space 3} 38.58144
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2} 10.27163{col 26}{space 2}  2.94892{col 37}{space 1}    3.48{col 46}{space 3}0.000{col 54}{space 4} 4.491855{col 67}{space 3} 16.05141
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-501.4071{col 26}{space 2} 164.1788{col 37}{space 1}   -3.05{col 46}{space 3}0.002{col 54}{space 4}-823.1916{col 67}{space 3}-179.6226
{txt}{space 8}size {c |}{col 14}{res}{space 2}-14.98261{col 26}{space 2} 23.16116{col 37}{space 1}   -0.65{col 46}{space 3}0.518{col 54}{space 4}-60.37766{col 67}{space 3} 30.41243
{txt}population~n {c |}{col 14}{res}{space 2}-1322.793{col 26}{space 2} 2289.016{col 37}{space 1}   -0.58{col 46}{space 3}0.563{col 54}{space 4}-5809.181{col 67}{space 3} 3163.596
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2} 1650.078{col 26}{space 2} 1601.441{col 37}{space 1}    1.03{col 46}{space 3}0.303{col 54}{space 4}-1488.688{col 67}{space 3} 4788.845
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2}-8060.077{col 26}{space 2}  5223.84{col 37}{space 1}   -1.54{col 46}{space 3}0.123{col 54}{space 4}-18298.62{col 67}{space 3} 2178.462
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 5184.901{col 26}{space 2} 811.5852{col 37}{space 1}    6.39{col 46}{space 3}0.000{col 54}{space 4} 3594.223{col 67}{space 3} 6775.578
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 7096.477{col 26}{space 2} 3785.111{col 37}{space 1}    1.87{col 46}{space 3}0.061{col 54}{space 4}-322.2052{col 67}{space 3} 14515.16
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2}-1522.275{col 26}{space 2} 4530.631{col 37}{space 1}   -0.34{col 46}{space 3}0.737{col 54}{space 4}-10402.15{col 67}{space 3} 7357.598
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2}  2310.14{col 26}{space 2} 2289.882{col 37}{space 1}    1.01{col 46}{space 3}0.313{col 54}{space 4}-2177.947{col 67}{space 3} 6798.227
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2}-744.4365{col 26}{space 2} 4640.307{col 37}{space 1}   -0.16{col 46}{space 3}0.873{col 54}{space 4}-9839.271{col 67}{space 3} 8350.398
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2} -2056.66{col 26}{space 2} 8171.462{col 37}{space 1}   -0.25{col 46}{space 3}0.801{col 54}{space 4}-18072.43{col 67}{space 3} 13959.11
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2}-127.6621{col 26}{space 2} 1333.273{col 37}{space 1}   -0.10{col 46}{space 3}0.924{col 54}{space 4}-2740.829{col 67}{space 3} 2485.505
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2} 1522.085{col 26}{space 2} 487.0724{col 37}{space 1}    3.12{col 46}{space 3}0.002{col 54}{space 4} 567.4402{col 67}{space 3} 2476.729
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2} 4608.269{col 26}{space 2} 947.6684{col 37}{space 1}    4.86{col 46}{space 3}0.000{col 54}{space 4} 2750.873{col 67}{space 3} 6465.665
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2} 1978.883{col 26}{space 2} 1505.944{col 37}{space 1}    1.31{col 46}{space 3}0.189{col 54}{space 4}-972.7132{col 67}{space 3} 4930.479
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2} 1172.977{col 26}{space 2} 410.7243{col 37}{space 1}    2.86{col 46}{space 3}0.004{col 54}{space 4} 367.9723{col 67}{space 3} 1977.982
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2}-2678.854{col 26}{space 2} 4388.405{col 37}{space 1}   -0.61{col 46}{space 3}0.542{col 54}{space 4}-11279.97{col 67}{space 3} 5922.262
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2} 3181.817{col 26}{space 2}  6188.97{col 37}{space 1}    0.51{col 46}{space 3}0.607{col 54}{space 4}-8948.341{col 67}{space 3} 15311.98
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2} 2170.584{col 26}{space 2} 7965.383{col 37}{space 1}    0.27{col 46}{space 3}0.785{col 54}{space 4}-13441.28{col 67}{space 3} 17782.45
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 5552.644{col 26}{space 2} 856.2242{col 37}{space 1}    6.49{col 46}{space 3}0.000{col 54}{space 4} 3874.476{col 67}{space 3} 7230.813
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2}  5316.56{col 26}{space 2} 1361.922{col 37}{space 1}    3.90{col 46}{space 3}0.000{col 54}{space 4} 2647.243{col 67}{space 3} 7985.877
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2} 4163.267{col 26}{space 2} 3720.253{col 37}{space 1}    1.12{col 46}{space 3}0.263{col 54}{space 4}-3128.294{col 67}{space 3} 11454.83
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2}  5270.27{col 26}{space 2}   1478.7{col 37}{space 1}    3.56{col 46}{space 3}0.000{col 54}{space 4} 2372.071{col 67}{space 3} 8168.469
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 6035.355{col 26}{space 2} 858.4919{col 37}{space 1}    7.03{col 46}{space 3}0.000{col 54}{space 4} 4352.741{col 67}{space 3} 7717.968
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2} 3795.814{col 26}{space 2} 4765.837{col 37}{space 1}    0.80{col 46}{space 3}0.426{col 54}{space 4}-5545.055{col 67}{space 3} 13136.68
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2} 4766.637{col 26}{space 2} 3264.786{col 37}{space 1}    1.46{col 46}{space 3}0.144{col 54}{space 4}-1632.227{col 67}{space 3}  11165.5
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2} 4930.735{col 26}{space 2} 2290.179{col 37}{space 1}    2.15{col 46}{space 3}0.031{col 54}{space 4} 442.0672{col 67}{space 3} 9419.403
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 17106.86{col 26}{space 2} 36308.63{col 37}{space 1}    0.47{col 46}{space 3}0.638{col 54}{space 4}-54056.75{col 67}{space 3} 88270.46
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .6014171{txt} {res} .7967839{txt} {res} .7339317{txt} {res} .7148585{txt} {res} .5827765{txt} ... {res} .4395463
{txt}{hline 78}

{com}. *10 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(2);

Condition: sscouncil_pct=2
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 505.1304{col 24} 184.7997{col 38} 2.733{col 47}0.006{col 58} 142.9296{col 70} 867.3312
------------------------------------------------------------------------------
{txt}
{com}. *25 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(3.5);

Condition: sscouncil_pct=3.5
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 502.4095{col 24} 170.2401{col 38} 2.951{col 47}0.003{col 58}  168.745{col 70} 836.0739
------------------------------------------------------------------------------
{txt}
{com}. *50 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(5.7);

Condition: sscouncil_pct=5.7
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 498.4188{col 24} 157.6637{col 38} 3.161{col 47}0.002{col 58} 189.4035{col 70}  807.434
------------------------------------------------------------------------------
{txt}
{com}. *75 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(11.7);

Condition: sscouncil_pct=11.7
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13}  487.535{col 24} 185.7697{col 38} 2.624{col 47}0.009{col 58} 123.4332{col 70} 851.6369
------------------------------------------------------------------------------
{txt}
{com}. *90 percentile;
. interact conflict_acc ssconflict, cond(sscouncil_pct) val(13.4);

Condition: sscouncil_pct=13.4
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 484.4513{col 24} 206.8953{col 38} 2.342{col 47}0.019{col 58} 78.94398{col 70} 889.9586
------------------------------------------------------------------------------
{txt}
{com}. ***********
> **Table 3**;
. ***********
> #delimit ;
. xtpcse ctot_pct conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion  employ_agriculture_ln sscouncil_pct 
>         eusupport conflictsupport newmember  size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 3,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.08; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      402
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.08
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.8709
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}31{txt}){col 68}= {res} 8.53e+06
{txt}Estimated coefficients{col 28}= {res}       38{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}    ctot_pct{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} .2393583{col 26}{space 2}  .429432{col 37}{space 1}    0.56{col 46}{space 3}0.577{col 54}{space 4}-.6023128{col 67}{space 3} 1.081029
{txt}extraordin~y {c |}{col 14}{res}{space 2} .2930151{col 26}{space 2}  .090459{col 37}{space 1}    3.24{col 46}{space 3}0.001{col 54}{space 4} .1157187{col 67}{space 3} .4703115
{txt}conflict_new {c |}{col 14}{res}{space 2}-2.787545{col 26}{space 2}  .528253{col 37}{space 1}   -5.28{col 46}{space 3}0.000{col 54}{space 4}-3.822902{col 67}{space 3}-1.752188
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2}-.2466612{col 26}{space 2} .0689455{col 37}{space 1}   -3.58{col 46}{space 3}0.000{col 54}{space 4}-.3817919{col 67}{space 3}-.1115304
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} .0299418{col 26}{space 2} .0050661{col 37}{space 1}    5.91{col 46}{space 3}0.000{col 54}{space 4} .0200125{col 67}{space 3} .0398711
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2}-.1651004{col 26}{space 2} .2529538{col 37}{space 1}   -0.65{col 46}{space 3}0.514{col 54}{space 4}-.6608806{col 67}{space 3} .3306799
{txt}employ_agr~n {c |}{col 14}{res}{space 2}  .509147{col 26}{space 2} .3176536{col 37}{space 1}    1.60{col 46}{space 3}0.109{col 54}{space 4}-.1134426{col 67}{space 3} 1.131736
{txt}sscouncil_~t {c |}{col 14}{res}{space 2} .4986632{col 26}{space 2} .0496099{col 37}{space 1}   10.05{col 46}{space 3}0.000{col 54}{space 4} .4014295{col 67}{space 3} .5958969
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2}-.0094859{col 26}{space 2} .0034924{col 37}{space 1}   -2.72{col 46}{space 3}0.007{col 54}{space 4} -.016331{col 67}{space 3}-.0026409
{txt}conflictsu~t {c |}{col 14}{res}{space 2} .0045582{col 26}{space 2} .0078511{col 37}{space 1}    0.58{col 46}{space 3}0.562{col 54}{space 4}-.0108297{col 67}{space 3}  .019946
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-.4527507{col 26}{space 2} .1348311{col 37}{space 1}   -3.36{col 46}{space 3}0.001{col 54}{space 4}-.7170147{col 67}{space 3}-.1884867
{txt}{space 8}size {c |}{col 14}{res}{space 2}-.0609867{col 26}{space 2} .0262839{col 37}{space 1}   -2.32{col 46}{space 3}0.020{col 54}{space 4}-.1125021{col 67}{space 3}-.0094712
{txt}population~n {c |}{col 14}{res}{space 2}-11.17077{col 26}{space 2} 2.409284{col 37}{space 1}   -4.64{col 46}{space 3}0.000{col 54}{space 4}-15.89288{col 67}{space 3}-6.448655
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2}-7.752709{col 26}{space 2} 1.562677{col 37}{space 1}   -4.96{col 46}{space 3}0.000{col 54}{space 4} -10.8155{col 67}{space 3}-4.689918
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2} 27.40541{col 26}{space 2}  5.41968{col 37}{space 1}    5.06{col 46}{space 3}0.000{col 54}{space 4} 16.78303{col 67}{space 3} 38.02779
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 4.389511{col 26}{space 2} .8026861{col 37}{space 1}    5.47{col 46}{space 3}0.000{col 54}{space 4} 2.816275{col 67}{space 3} 5.962747
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2}  23.8316{col 26}{space 2} 3.655214{col 37}{space 1}    6.52{col 46}{space 3}0.000{col 54}{space 4} 16.66751{col 67}{space 3} 30.99569
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2} 25.96639{col 26}{space 2} 4.609495{col 37}{space 1}    5.63{col 46}{space 3}0.000{col 54}{space 4} 16.93195{col 67}{space 3} 35.00083
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2}-9.153088{col 26}{space 2} 2.496369{col 37}{space 1}   -3.67{col 46}{space 3}0.000{col 54}{space 4}-14.04588{col 67}{space 3}-4.260294
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2} 23.51449{col 26}{space 2} 4.597402{col 37}{space 1}    5.11{col 46}{space 3}0.000{col 54}{space 4} 14.50375{col 67}{space 3} 32.52524
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2}-37.16794{col 26}{space 2} 8.091158{col 37}{space 1}   -4.59{col 46}{space 3}0.000{col 54}{space 4}-53.02631{col 67}{space 3}-21.30956
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2} 6.576737{col 26}{space 2} 1.255909{col 37}{space 1}    5.24{col 46}{space 3}0.000{col 54}{space 4}   4.1152{col 67}{space 3} 9.038274
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2}-3.514073{col 26}{space 2} .6568505{col 37}{space 1}   -5.35{col 46}{space 3}0.000{col 54}{space 4}-4.801476{col 67}{space 3}-2.226669
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2} 3.326396{col 26}{space 2} .8118198{col 37}{space 1}    4.10{col 46}{space 3}0.000{col 54}{space 4} 1.735258{col 67}{space 3} 4.917533
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2}-7.769444{col 26}{space 2} 1.632155{col 37}{space 1}   -4.76{col 46}{space 3}0.000{col 54}{space 4}-10.96841{col 67}{space 3}-4.570478
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2}-2.543954{col 26}{space 2} .4610468{col 37}{space 1}   -5.52{col 46}{space 3}0.000{col 54}{space 4}-3.447589{col 67}{space 3}-1.640319
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2} 20.79273{col 26}{space 2} 4.493166{col 37}{space 1}    4.63{col 46}{space 3}0.000{col 54}{space 4} 11.98629{col 67}{space 3} 29.59918
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2}-24.02419{col 26}{space 2} 6.639001{col 37}{space 1}   -3.62{col 46}{space 3}0.000{col 54}{space 4}-37.03639{col 67}{space 3}-11.01199
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2}-28.98207{col 26}{space 2}  8.43359{col 37}{space 1}   -3.44{col 46}{space 3}0.001{col 54}{space 4}-45.51161{col 67}{space 3}-12.45254
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 4.893793{col 26}{space 2} .7929969{col 37}{space 1}    6.17{col 46}{space 3}0.000{col 54}{space 4} 3.339548{col 67}{space 3} 6.448039
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 4.330105{col 26}{space 2} 1.432625{col 37}{space 1}    3.02{col 46}{space 3}0.003{col 54}{space 4} 1.522212{col 67}{space 3} 7.137998
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2}-12.92051{col 26}{space 2} 4.146494{col 37}{space 1}   -3.12{col 46}{space 3}0.002{col 54}{space 4}-21.04749{col 67}{space 3}-4.793536
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2}-1.196488{col 26}{space 2} 1.900123{col 37}{space 1}   -0.63{col 46}{space 3}0.529{col 54}{space 4} -4.92066{col 67}{space 3} 2.527684
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 5.047611{col 26}{space 2} .8293736{col 37}{space 1}    6.09{col 46}{space 3}0.000{col 54}{space 4} 3.422068{col 67}{space 3} 6.673153
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2}-16.17704{col 26}{space 2} 5.255419{col 37}{space 1}   -3.08{col 46}{space 3}0.002{col 54}{space 4}-26.47747{col 67}{space 3}-5.876605
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2}-10.53734{col 26}{space 2}  3.84917{col 37}{space 1}   -2.74{col 46}{space 3}0.006{col 54}{space 4}-18.08157{col 67}{space 3}-2.993103
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2}-6.373363{col 26}{space 2} 2.874864{col 37}{space 1}   -2.22{col 46}{space 3}0.027{col 54}{space 4}-12.00799{col 67}{space 3}-.7387337
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 179.4247{col 26}{space 2} 38.66231{col 37}{space 1}    4.64{col 46}{space 3}0.000{col 54}{space 4}  103.648{col 67}{space 3} 255.2014
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res}    .5197{txt} {res} .6856951{txt} {res} .6272459{txt} {res} .6476795{txt} {res} .5707651{txt} ... {res} .4841399
{txt}{hline 78}

{com}. *10 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(14);

Condition: eusupport=14
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .3031726{col 24} .3234583{col 38} 0.937{col 47}0.349{col 58}-.3307941{col 70} .9371394
------------------------------------------------------------------------------
{txt}
{com}. *25 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(29);

Condition: eusupport=29
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .3715451{col 24} .2143666{col 38} 1.733{col 47}0.083{col 58}-.0486057{col 70}  .791696
------------------------------------------------------------------------------
{txt}
{com}. *50 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(48);

Condition: eusupport=48
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .4581503{col 24} .1070239{col 38} 4.281{col 47}0.000{col 58} .2483873{col 70} .6679133
------------------------------------------------------------------------------
{txt}
{com}. *75 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(64);

Condition: eusupport=64
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .5310809{col 24} .1300793{col 38} 4.083{col 47}0.000{col 58} .2761301{col 70} .7860317
------------------------------------------------------------------------------
{txt}
{com}. *90 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(73);

Condition: eusupport=73
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} .5721044{col 24} .1840231{col 38} 3.109{col 47}0.002{col 58} .2114258{col 70}  .932783
------------------------------------------------------------------------------
{txt}
{com}. xtpcse ctotnet conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion  employ_agriculture_ln sscouncil_pct 
>         eusupport conflictsupport   newmember size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 2,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.04; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      401
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.04
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.6909
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}29{txt}){col 68}= {res}189020.57
{txt}Estimated coefficients{col 28}= {res}       38{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}     ctotnet{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2}-387.7013{col 26}{space 2} 449.2067{col 37}{space 1}   -0.86{col 46}{space 3}0.388{col 54}{space 4} -1268.13{col 67}{space 3} 492.7276
{txt}extraordin~y {c |}{col 14}{res}{space 2} 463.6055{col 26}{space 2} 134.4913{col 37}{space 1}    3.45{col 46}{space 3}0.001{col 54}{space 4} 200.0074{col 67}{space 3} 727.2035
{txt}conflict_new {c |}{col 14}{res}{space 2}-2525.122{col 26}{space 2} 590.4922{col 37}{space 1}   -4.28{col 46}{space 3}0.000{col 54}{space 4}-3682.466{col 67}{space 3}-1367.779
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2}-86.53505{col 26}{space 2} 68.47324{col 37}{space 1}   -1.26{col 46}{space 3}0.206{col 54}{space 4}-220.7401{col 67}{space 3} 47.67004
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} 2.455832{col 26}{space 2} 4.955843{col 37}{space 1}    0.50{col 46}{space 3}0.620{col 54}{space 4}-7.257443{col 67}{space 3} 12.16911
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2} 377.4178{col 26}{space 2} 242.6917{col 37}{space 1}    1.56{col 46}{space 3}0.120{col 54}{space 4}-98.24925{col 67}{space 3} 853.0849
{txt}employ_agr~n {c |}{col 14}{res}{space 2}-89.04768{col 26}{space 2} 313.6304{col 37}{space 1}   -0.28{col 46}{space 3}0.776{col 54}{space 4} -703.752{col 67}{space 3} 525.6566
{txt}sscouncil_~t {c |}{col 14}{res}{space 2} 408.4706{col 26}{space 2} 42.78458{col 37}{space 1}    9.55{col 46}{space 3}0.000{col 54}{space 4} 324.6143{col 67}{space 3} 492.3268
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2} 10.14006{col 26}{space 2} 3.064354{col 37}{space 1}    3.31{col 46}{space 3}0.001{col 54}{space 4} 4.134038{col 67}{space 3} 16.14609
{txt}conflictsu~t {c |}{col 14}{res}{space 2} 16.41439{col 26}{space 2}  7.86566{col 37}{space 1}    2.09{col 46}{space 3}0.037{col 54}{space 4} .9979806{col 67}{space 3}  31.8308
{txt}{space 3}newmember {c |}{col 14}{res}{space 2} -560.021{col 26}{space 2}  162.616{col 37}{space 1}   -3.44{col 46}{space 3}0.001{col 54}{space 4}-878.7424{col 67}{space 3}-241.2996
{txt}{space 8}size {c |}{col 14}{res}{space 2}-10.31096{col 26}{space 2} 23.87404{col 37}{space 1}   -0.43{col 46}{space 3}0.666{col 54}{space 4}-57.10321{col 67}{space 3} 36.48129
{txt}population~n {c |}{col 14}{res}{space 2}-1667.896{col 26}{space 2} 2046.566{col 37}{space 1}   -0.81{col 46}{space 3}0.415{col 54}{space 4}-5679.092{col 67}{space 3} 2343.301
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2}  1482.12{col 26}{space 2} 1451.599{col 37}{space 1}    1.02{col 46}{space 3}0.307{col 54}{space 4}-1362.962{col 67}{space 3} 4327.202
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2}-7179.545{col 26}{space 2} 4609.856{col 37}{space 1}   -1.56{col 46}{space 3}0.119{col 54}{space 4} -16214.7{col 67}{space 3} 1855.607
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 5270.749{col 26}{space 2} 888.8094{col 37}{space 1}    5.93{col 46}{space 3}0.000{col 54}{space 4} 3528.715{col 67}{space 3} 7012.784
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 7664.485{col 26}{space 2} 3538.146{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} 729.8457{col 67}{space 3} 14599.12
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2}-772.6312{col 26}{space 2}  4004.11{col 37}{space 1}   -0.19{col 46}{space 3}0.847{col 54}{space 4}-8620.542{col 67}{space 3}  7075.28
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2} 1975.202{col 26}{space 2} 2008.686{col 37}{space 1}    0.98{col 46}{space 3}0.325{col 54}{space 4} -1961.75{col 67}{space 3} 5912.153
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2} -14.2168{col 26}{space 2}  4126.82{col 37}{space 1}   -0.00{col 46}{space 3}0.997{col 54}{space 4}-8102.636{col 67}{space 3} 8074.203
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2}-3313.408{col 26}{space 2} 7334.228{col 37}{space 1}   -0.45{col 46}{space 3}0.651{col 54}{space 4}-17688.23{col 67}{space 3} 11061.42
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2} 72.65526{col 26}{space 2}  1234.53{col 37}{space 1}    0.06{col 46}{space 3}0.953{col 54}{space 4}-2346.979{col 67}{space 3}  2492.29
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2} 1566.679{col 26}{space 2} 468.4542{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4} 648.5253{col 67}{space 3} 2484.832
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2}  4671.43{col 26}{space 2} 1019.656{col 37}{space 1}    4.58{col 46}{space 3}0.000{col 54}{space 4}  2672.94{col 67}{space 3} 6669.919
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2} 1807.761{col 26}{space 2} 1353.471{col 37}{space 1}    1.34{col 46}{space 3}0.182{col 54}{space 4}-844.9927{col 67}{space 3} 4460.515
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2} 1214.907{col 26}{space 2} 376.3843{col 37}{space 1}    3.23{col 46}{space 3}0.001{col 54}{space 4}  477.207{col 67}{space 3} 1952.606
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2} -1973.24{col 26}{space 2} 3857.858{col 37}{space 1}   -0.51{col 46}{space 3}0.609{col 54}{space 4}-9534.503{col 67}{space 3} 5588.023
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2} 2148.346{col 26}{space 2} 5383.644{col 37}{space 1}    0.40{col 46}{space 3}0.690{col 54}{space 4}-8403.402{col 67}{space 3} 12700.09
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2} 768.1452{col 26}{space 2} 6960.936{col 37}{space 1}    0.11{col 46}{space 3}0.912{col 54}{space 4}-12875.04{col 67}{space 3} 14411.33
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 5505.503{col 26}{space 2} 828.9016{col 37}{space 1}    6.64{col 46}{space 3}0.000{col 54}{space 4} 3880.885{col 67}{space 3}  7130.12
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 5402.648{col 26}{space 2} 1429.246{col 37}{space 1}    3.78{col 46}{space 3}0.000{col 54}{space 4} 2601.378{col 67}{space 3} 8203.918
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2}  3523.41{col 26}{space 2} 3110.359{col 37}{space 1}    1.13{col 46}{space 3}0.257{col 54}{space 4}-2572.782{col 67}{space 3} 9619.602
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2} 4964.398{col 26}{space 2} 1114.003{col 37}{space 1}    4.46{col 46}{space 3}0.000{col 54}{space 4} 2780.993{col 67}{space 3} 7147.804
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 5980.546{col 26}{space 2} 845.9702{col 37}{space 1}    7.07{col 46}{space 3}0.000{col 54}{space 4} 4322.475{col 67}{space 3} 7638.617
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2}  2944.45{col 26}{space 2} 4026.481{col 37}{space 1}    0.73{col 46}{space 3}0.465{col 54}{space 4}-4947.308{col 67}{space 3} 10836.21
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2} 4175.083{col 26}{space 2} 2678.168{col 37}{space 1}    1.56{col 46}{space 3}0.119{col 54}{space 4} -1074.03{col 67}{space 3} 9424.196
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2} 4507.092{col 26}{space 2} 1829.396{col 37}{space 1}    2.46{col 46}{space 3}0.014{col 54}{space 4} 921.5413{col 67}{space 3} 8092.643
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 22514.83{col 26}{space 2} 32358.08{col 37}{space 1}    0.70{col 46}{space 3}0.487{col 54}{space 4}-40905.84{col 67}{space 3}  85935.5
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .6213155{txt} {res}  .797547{txt} {res} .7374648{txt} {res} .7270645{txt} {res} .5812619{txt} ... {res} .4380384
{txt}{hline 78}

{com}. *10 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(14);

Condition: eusupport=14
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13}-157.8998{col 24}   347.86{col 38}-0.454{col 47}0.650{col 58}-839.6929{col 70} 523.8933
------------------------------------------------------------------------------
{txt}
{com}. *25 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(29);

Condition: eusupport=29
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 88.31606{col 24} 247.7284{col 38} 0.357{col 47}0.721{col 58}-397.2227{col 70} 573.8548
------------------------------------------------------------------------------
{txt}
{com}. *50 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(48);

Condition: eusupport=48
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 400.1895{col 24} 160.6114{col 38} 2.492{col 47}0.013{col 58} 85.39701{col 70}  714.982
------------------------------------------------------------------------------
{txt}
{com}. *75 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(64);

Condition: eusupport=64
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 662.8198{col 24} 174.6022{col 38} 3.796{col 47}0.000{col 58} 320.6058{col 70} 1005.034
------------------------------------------------------------------------------
{txt}
{com}. *90 percentile;
. interact conflict_acc conflictsupport, cond(eusupport) val(73);

Condition: eusupport=73
Model    : regress

------------------------------------------------------------------------------
 ctotnet |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
conflict_acc |{col 13} 810.5493{col 24} 216.8973{col 38} 3.737{col 47}0.000{col 58} 385.4384{col 70}  1235.66
------------------------------------------------------------------------------
{txt}
{com}. ***************;
. ***Appendix****;
. ***************;
. #delimit ;
{txt}delimiter now ;
{com}. xtpcse ctot_pct conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion gdp_cohesion employ_agriculture_ln sscouncil_pct 
>         eusupport newmember  size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 3,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.08; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      402
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.08
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.8728
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}31{txt}){col 68}= {res} 2.85e+08
{txt}Estimated coefficients{col 28}= {res}       38{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}    ctot_pct{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} .3117046{col 26}{space 2} .1156405{col 37}{space 1}    2.70{col 46}{space 3}0.007{col 54}{space 4} .0850534{col 67}{space 3} .5383558
{txt}extraordin~y {c |}{col 14}{res}{space 2}    .1708{col 26}{space 2} .1142523{col 37}{space 1}    1.49{col 46}{space 3}0.135{col 54}{space 4}-.0531303{col 67}{space 3} .3947303
{txt}conflict_new {c |}{col 14}{res}{space 2}-2.958087{col 26}{space 2} .4674137{col 37}{space 1}   -6.33{col 46}{space 3}0.000{col 54}{space 4}-3.874201{col 67}{space 3}-2.041973
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2} -.207288{col 26}{space 2} .0532985{col 37}{space 1}   -3.89{col 46}{space 3}0.000{col 54}{space 4}-.3117511{col 67}{space 3}-.1028249
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} .0290976{col 26}{space 2} .0043942{col 37}{space 1}    6.62{col 46}{space 3}0.000{col 54}{space 4} .0204851{col 67}{space 3}   .03771
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2}-5.445156{col 26}{space 2} .9203053{col 37}{space 1}   -5.92{col 46}{space 3}0.000{col 54}{space 4}-7.248922{col 67}{space 3}-3.641391
{txt}gdp_cohesion {c |}{col 14}{res}{space 2} .0781579{col 26}{space 2} .0141123{col 37}{space 1}    5.54{col 46}{space 3}0.000{col 54}{space 4} .0504983{col 67}{space 3} .1058174
{txt}employ_agr~n {c |}{col 14}{res}{space 2} .7941762{col 26}{space 2} .2719645{col 37}{space 1}    2.92{col 46}{space 3}0.003{col 54}{space 4} .2611355{col 67}{space 3} 1.327217
{txt}sscouncil_~t {c |}{col 14}{res}{space 2} .5010625{col 26}{space 2}  .056394{col 37}{space 1}    8.89{col 46}{space 3}0.000{col 54}{space 4} .3905324{col 67}{space 3} .6115926
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2}-.0105345{col 26}{space 2} .0036629{col 37}{space 1}   -2.88{col 46}{space 3}0.004{col 54}{space 4}-.0177136{col 67}{space 3}-.0033554
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-.2799151{col 26}{space 2}  .144201{col 37}{space 1}   -1.94{col 46}{space 3}0.052{col 54}{space 4}-.5625439{col 67}{space 3} .0027136
{txt}{space 8}size {c |}{col 14}{res}{space 2}-.0595888{col 26}{space 2} .0224722{col 37}{space 1}   -2.65{col 46}{space 3}0.008{col 54}{space 4}-.1036335{col 67}{space 3}-.0155441
{txt}population~n {c |}{col 14}{res}{space 2} -11.5326{col 26}{space 2} 2.286427{col 37}{space 1}   -5.04{col 46}{space 3}0.000{col 54}{space 4}-16.01391{col 67}{space 3}-7.051281
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2}-8.113479{col 26}{space 2} 1.518608{col 37}{space 1}   -5.34{col 46}{space 3}0.000{col 54}{space 4} -11.0899{col 67}{space 3}-5.137062
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2} 27.47538{col 26}{space 2} 5.211519{col 37}{space 1}    5.27{col 46}{space 3}0.000{col 54}{space 4} 17.26099{col 67}{space 3} 37.68976
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 5.080213{col 26}{space 2} .7702903{col 37}{space 1}    6.60{col 46}{space 3}0.000{col 54}{space 4} 3.570472{col 67}{space 3} 6.589955
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 23.78112{col 26}{space 2} 3.470471{col 37}{space 1}    6.85{col 46}{space 3}0.000{col 54}{space 4} 16.97912{col 67}{space 3} 30.58312
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2} 25.84863{col 26}{space 2} 4.449486{col 37}{space 1}    5.81{col 46}{space 3}0.000{col 54}{space 4}  17.1278{col 67}{space 3} 34.56946
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2}-9.527362{col 26}{space 2} 2.391814{col 37}{space 1}   -3.98{col 46}{space 3}0.000{col 54}{space 4}-14.21523{col 67}{space 3}-4.839492
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2}  23.4388{col 26}{space 2} 4.444136{col 37}{space 1}    5.27{col 46}{space 3}0.000{col 54}{space 4} 14.72846{col 67}{space 3} 32.14915
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2} -37.4208{col 26}{space 2} 7.771679{col 37}{space 1}   -4.82{col 46}{space 3}0.000{col 54}{space 4}-52.65301{col 67}{space 3}-22.18859
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2} 6.474299{col 26}{space 2} 1.178502{col 37}{space 1}    5.49{col 46}{space 3}0.000{col 54}{space 4} 4.164477{col 67}{space 3}  8.78412
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2}-3.992793{col 26}{space 2} .5910847{col 37}{space 1}   -6.76{col 46}{space 3}0.000{col 54}{space 4}-5.151298{col 67}{space 3}-2.834288
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2} 4.373467{col 26}{space 2} 1.282483{col 37}{space 1}    3.41{col 46}{space 3}0.001{col 54}{space 4} 1.859846{col 67}{space 3} 6.887088
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2}-8.289467{col 26}{space 2} 1.519726{col 37}{space 1}   -5.45{col 46}{space 3}0.000{col 54}{space 4}-11.26808{col 67}{space 3}-5.310858
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2}-2.764378{col 26}{space 2} .4540656{col 37}{space 1}   -6.09{col 46}{space 3}0.000{col 54}{space 4} -3.65433{col 67}{space 3}-1.874425
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2} 20.86026{col 26}{space 2} 4.351972{col 37}{space 1}    4.79{col 46}{space 3}0.000{col 54}{space 4} 12.33055{col 67}{space 3} 29.38997
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2}-24.53291{col 26}{space 2} 6.350624{col 37}{space 1}   -3.86{col 46}{space 3}0.000{col 54}{space 4} -36.9799{col 67}{space 3}-12.08591
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2}-28.17855{col 26}{space 2} 8.117462{col 37}{space 1}   -3.47{col 46}{space 3}0.001{col 54}{space 4}-44.08848{col 67}{space 3}-12.26861
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 6.422345{col 26}{space 2}  .876833{col 37}{space 1}    7.32{col 46}{space 3}0.000{col 54}{space 4} 4.703784{col 67}{space 3} 8.140906
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 6.362045{col 26}{space 2} 1.419555{col 37}{space 1}    4.48{col 46}{space 3}0.000{col 54}{space 4} 3.579768{col 67}{space 3} 9.144323
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2}-13.20507{col 26}{space 2} 4.013793{col 37}{space 1}   -3.29{col 46}{space 3}0.001{col 54}{space 4}-21.07195{col 67}{space 3}-5.338176
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2} 1.209749{col 26}{space 2} 2.019988{col 37}{space 1}    0.60{col 46}{space 3}0.549{col 54}{space 4}-2.749356{col 67}{space 3} 5.168853
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 6.954992{col 26}{space 2} .9768862{col 37}{space 1}    7.12{col 46}{space 3}0.000{col 54}{space 4}  5.04033{col 67}{space 3} 8.869654
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2}-14.33984{col 26}{space 2} 5.162185{col 37}{space 1}   -2.78{col 46}{space 3}0.005{col 54}{space 4}-24.45753{col 67}{space 3}-4.222139
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2}-8.049021{col 26}{space 2} 3.867745{col 37}{space 1}   -2.08{col 46}{space 3}0.037{col 54}{space 4}-15.62966{col 67}{space 3}-.4683797
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2}-3.951633{col 26}{space 2} 2.935914{col 37}{space 1}   -1.35{col 46}{space 3}0.178{col 54}{space 4}-9.705918{col 67}{space 3} 1.802653
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 186.0469{col 26}{space 2} 36.68074{col 37}{space 1}    5.07{col 46}{space 3}0.000{col 54}{space 4}  114.154{col 67}{space 3} 257.9398
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .5473728{txt} {res} .6688415{txt} {res} .6292257{txt} {res} .6044021{txt} {res} .5866221{txt} ... {res} .4924556
{txt}{hline 78}

{com}. interact gdppercap_eu100 gdp_cohesion, cond(cohesion) val(0);

Condition: cohesion=0
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
gdppercap_eu100 |{col 13} .0290976{col 24} .0043942{col 38} 6.622{col 47}0.000{col 58} .0204851{col 70}   .03771
------------------------------------------------------------------------------
{txt}
{com}. interact gdppercap_eu100 gdp_cohesion, cond(cohesion) val(1);

Condition: cohesion=1
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
gdppercap_eu100 |{col 13} .1072554{col 24} .0162771{col 38} 6.589{col 47}0.000{col 58} .0753529{col 70} .1391579
------------------------------------------------------------------------------
{txt}
{com}. xtpcse ctot_pct conflict_acc extraordinary conflict_new enlargement gdppercap_eu100 cohesion cohesion_population employ_agriculture_ln sscouncil_pct 
>         eusupport newmember  size population_ln id_*, correlation(psar1);

{txt}Number of gaps in sample:  {res}2
{txt}(note: computations for rho restarted at each gap)
(note: the number of observations per panel, e(n_sigma) = 3,
       used to compute the disturbance of covariance matrix e(Sigma)
       is less than half of the average number of observations per panel,
       e(n_avg) = 16.08; you may want to consider the pairwise option)
{res}
{txt}Prais-Winsten regression, correlated panels corrected standard errors (PCSEs)

Group variable:{col 19}{res}id{col 49}{txt}Number of obs{col 68}= {res}      402
{txt}Time variable:{col 19}{res}year{col 49}{txt}Number of groups{col 68}= {res}       25
{txt}Panels:{col 19}{res}correlated (unbalanced){col 49}{txt}Obs per group: min{col 68}= {res}        3
{txt}Autocorrelation:{col 19}{res}panel-specific AR(1){col 64}{txt}avg{col 68}= {res}    16.08
{txt}Sigma computed by {col 19}{res}casewise selection{txt}{col 64}max{col 68}= {res}       30
{txt}Estimated covariances{col 28}= {res}      325{col 49}{txt}R-squared{col 68}= {res}   0.8697
{txt}Estimated autocorrelations{col 28}= {res}       25{col 49}{txt}Wald chi2({res}31{txt}){col 68}= {res} 1.22e+06
{txt}Estimated coefficients{col 28}= {res}       38{col 49}{txt}Prob > chi2{col 68}= {res}   0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}Panel-corrected
{col 1}    ctot_pct{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
conflict_acc {c |}{col 14}{res}{space 2} .4070505{col 26}{space 2} .1071118{col 37}{space 1}    3.80{col 46}{space 3}0.000{col 54}{space 4} .1971153{col 67}{space 3} .6169858
{txt}extraordin~y {c |}{col 14}{res}{space 2} .1589836{col 26}{space 2} .1097414{col 37}{space 1}    1.45{col 46}{space 3}0.147{col 54}{space 4}-.0561056{col 67}{space 3} .3740727
{txt}conflict_new {c |}{col 14}{res}{space 2}-2.699991{col 26}{space 2} .5536174{col 37}{space 1}   -4.88{col 46}{space 3}0.000{col 54}{space 4}-3.785061{col 67}{space 3}-1.614921
{txt}{space 1}enlargement {c |}{col 14}{res}{space 2}-.2582158{col 26}{space 2} .0620781{col 37}{space 1}   -4.16{col 46}{space 3}0.000{col 54}{space 4}-.3798866{col 67}{space 3} -.136545
{txt}gdpperca~100 {c |}{col 14}{res}{space 2} .0283107{col 26}{space 2} .0048498{col 37}{space 1}    5.84{col 46}{space 3}0.000{col 54}{space 4} .0188052{col 67}{space 3} .0378162
{txt}{space 4}cohesion {c |}{col 14}{res}{space 2} 11.14066{col 26}{space 2} 2.638497{col 37}{space 1}    4.22{col 46}{space 3}0.000{col 54}{space 4} 5.969298{col 67}{space 3} 16.31202
{txt}cohesion_p~n {c |}{col 14}{res}{space 2}-.6838317{col 26}{space 2} .1634403{col 37}{space 1}   -4.18{col 46}{space 3}0.000{col 54}{space 4}-1.004169{col 67}{space 3}-.3634946
{txt}employ_agr~n {c |}{col 14}{res}{space 2} .5779216{col 26}{space 2} .3131785{col 37}{space 1}    1.85{col 46}{space 3}0.065{col 54}{space 4}-.0358969{col 67}{space 3}  1.19174
{txt}sscouncil_~t {c |}{col 14}{res}{space 2}  .561291{col 26}{space 2} .0525504{col 37}{space 1}   10.68{col 46}{space 3}0.000{col 54}{space 4}  .458294{col 67}{space 3} .6642879
{txt}{space 3}eusupport {c |}{col 14}{res}{space 2} -.009055{col 26}{space 2} .0034313{col 37}{space 1}   -2.64{col 46}{space 3}0.008{col 54}{space 4}-.0157803{col 67}{space 3}-.0023297
{txt}{space 3}newmember {c |}{col 14}{res}{space 2}-.5073723{col 26}{space 2} .1111199{col 37}{space 1}   -4.57{col 46}{space 3}0.000{col 54}{space 4}-.7251634{col 67}{space 3}-.2895812
{txt}{space 8}size {c |}{col 14}{res}{space 2}-.0452019{col 26}{space 2} .0252517{col 37}{space 1}   -1.79{col 46}{space 3}0.073{col 54}{space 4}-.0946943{col 67}{space 3} .0042906
{txt}population~n {c |}{col 14}{res}{space 2}-8.893312{col 26}{space 2} 2.433401{col 37}{space 1}   -3.65{col 46}{space 3}0.000{col 54}{space 4}-13.66269{col 67}{space 3}-4.123934
{txt}{space 8}id_2 {c |}{col 14}{res}{space 2}-6.053986{col 26}{space 2}  1.60466{col 37}{space 1}   -3.77{col 46}{space 3}0.000{col 54}{space 4}-9.199061{col 67}{space 3}-2.908911
{txt}{space 8}id_3 {c |}{col 14}{res}{space 2} 22.10152{col 26}{space 2}  5.58302{col 37}{space 1}    3.96{col 46}{space 3}0.000{col 54}{space 4}   11.159{col 67}{space 3} 33.04404
{txt}{space 8}id_4 {c |}{col 14}{res}{space 2} 3.841536{col 26}{space 2} .8117271{col 37}{space 1}    4.73{col 46}{space 3}0.000{col 54}{space 4}  2.25058{col 67}{space 3} 5.432492
{txt}{space 8}id_5 {c |}{col 14}{res}{space 2} 20.70919{col 26}{space 2} 3.755752{col 37}{space 1}    5.51{col 46}{space 3}0.000{col 54}{space 4} 13.34805{col 67}{space 3} 28.07033
{txt}{space 8}id_6 {c |}{col 14}{res}{space 2} 21.39805{col 26}{space 2} 4.785674{col 37}{space 1}    4.47{col 46}{space 3}0.000{col 54}{space 4}  12.0183{col 67}{space 3} 30.77779
{txt}{space 8}id_7 {c |}{col 14}{res}{space 2}-7.267844{col 26}{space 2} 2.454467{col 37}{space 1}   -2.96{col 46}{space 3}0.003{col 54}{space 4}-12.07851{col 67}{space 3}-2.457176
{txt}{space 8}id_8 {c |}{col 14}{res}{space 2} 19.02221{col 26}{space 2} 4.784303{col 37}{space 1}    3.98{col 46}{space 3}0.000{col 54}{space 4} 9.645149{col 67}{space 3} 28.39927
{txt}{space 8}id_9 {c |}{col 14}{res}{space 2}-29.21993{col 26}{space 2} 8.361896{col 37}{space 1}   -3.49{col 46}{space 3}0.000{col 54}{space 4}-45.60895{col 67}{space 3}-12.83092
{txt}{space 7}id_10 {c |}{col 14}{res}{space 2}  5.60852{col 26}{space 2} 1.271894{col 37}{space 1}    4.41{col 46}{space 3}0.000{col 54}{space 4} 3.115654{col 67}{space 3} 8.101386
{txt}{space 7}id_11 {c |}{col 14}{res}{space 2}-2.917988{col 26}{space 2} .6184709{col 37}{space 1}   -4.72{col 46}{space 3}0.000{col 54}{space 4}-4.130169{col 67}{space 3}-1.705808
{txt}{space 7}id_12 {c |}{col 14}{res}{space 2} 2.802798{col 26}{space 2} .8305484{col 37}{space 1}    3.37{col 46}{space 3}0.001{col 54}{space 4} 1.174953{col 67}{space 3} 4.430643
{txt}{space 7}id_13 {c |}{col 14}{res}{space 2}-6.105857{col 26}{space 2} 1.633395{col 37}{space 1}   -3.74{col 46}{space 3}0.000{col 54}{space 4}-9.307253{col 67}{space 3}-2.904462
{txt}{space 7}id_14 {c |}{col 14}{res}{space 2} -2.11522{col 26}{space 2}  .470183{col 37}{space 1}   -4.50{col 46}{space 3}0.000{col 54}{space 4}-3.036762{col 67}{space 3}-1.193679
{txt}{space 7}id_15 {c |}{col 14}{res}{space 2}  16.3465{col 26}{space 2} 4.643739{col 37}{space 1}    3.52{col 46}{space 3}0.000{col 54}{space 4} 7.244939{col 67}{space 3} 25.44806
{txt}{space 7}id_16 {c |}{col 14}{res}{space 2}-17.92732{col 26}{space 2} 6.721977{col 37}{space 1}   -2.67{col 46}{space 3}0.008{col 54}{space 4}-31.10215{col 67}{space 3}-4.752486
{txt}{space 7}id_17 {c |}{col 14}{res}{space 2}-23.86165{col 26}{space 2} 8.370818{col 37}{space 1}   -2.85{col 46}{space 3}0.004{col 54}{space 4}-40.26815{col 67}{space 3}-7.455142
{txt}{space 7}id_18 {c |}{col 14}{res}{space 2} 4.380599{col 26}{space 2} .8825682{col 37}{space 1}    4.96{col 46}{space 3}0.000{col 54}{space 4} 2.650797{col 67}{space 3} 6.110401
{txt}{space 7}id_19 {c |}{col 14}{res}{space 2} 3.298574{col 26}{space 2} 1.536218{col 37}{space 1}    2.15{col 46}{space 3}0.032{col 54}{space 4} .2876422{col 67}{space 3} 6.309507
{txt}{space 7}id_20 {c |}{col 14}{res}{space 2} -10.5994{col 26}{space 2}  4.04266{col 37}{space 1}   -2.62{col 46}{space 3}0.009{col 54}{space 4}-18.52287{col 67}{space 3}-2.675935
{txt}{space 7}id_21 {c |}{col 14}{res}{space 2}-.5730896{col 26}{space 2}  1.83973{col 37}{space 1}   -0.31{col 46}{space 3}0.755{col 54}{space 4}-4.178894{col 67}{space 3} 3.032714
{txt}{space 7}id_22 {c |}{col 14}{res}{space 2} 4.552429{col 26}{space 2} .9174896{col 37}{space 1}    4.96{col 46}{space 3}0.000{col 54}{space 4} 2.754183{col 67}{space 3} 6.350676
{txt}{space 7}id_23 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_24 {c |}{col 14}{res}  (omitted)
{txt}{space 7}id_25 {c |}{col 14}{res}{space 2} -13.1967{col 26}{space 2}  5.15069{col 37}{space 1}   -2.56{col 46}{space 3}0.010{col 54}{space 4}-23.29187{col 67}{space 3}-3.101538
{txt}{space 7}id_26 {c |}{col 14}{res}{space 2}-8.519081{col 26}{space 2} 3.716855{col 37}{space 1}   -2.29{col 46}{space 3}0.022{col 54}{space 4}-15.80398{col 67}{space 3} -1.23418
{txt}{space 7}id_27 {c |}{col 14}{res}{space 2}-5.084165{col 26}{space 2} 2.746378{col 37}{space 1}   -1.85{col 46}{space 3}0.064{col 54}{space 4}-10.46697{col 67}{space 3} .2986361
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 142.4283{col 26}{space 2} 38.98042{col 37}{space 1}    3.65{col 46}{space 3}0.000{col 54}{space 4} 66.02804{col 67}{space 3} 218.8285
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        rhos = {res} .5193926{txt} {res} .6890484{txt} {res} .6230271{txt} {res} .6367167{txt} {res} .5681922{txt} ... {res} .5000371
{txt}{hline 78}

{com}. interact cohesion cohesion_population, cond(population) val(14.124);

Condition: population_ln=14.124
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
cohesion |{col 13} 1.482217{col 24} .3893637{col 38} 3.807{col 47}0.000{col 58} .7190786{col 70} 2.245356
------------------------------------------------------------------------------
{txt}
{com}. interact cohesion cohesion_population, cond(population) val(15.048);

Condition: population_ln=15.048
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
cohesion |{col 13} .8503568{col 24} .2784048{col 38} 3.054{col 47}0.002{col 58} .3046935{col 70}  1.39602
------------------------------------------------------------------------------
{txt}
{com}. interact cohesion cohesion_population, cond(population) val(16.116);

Condition: population_ln=16.116
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
cohesion |{col 13} .1200246{col 24} .2206745{col 38} 0.544{col 47}0.587{col 58}-.3124896{col 70} .5525387
------------------------------------------------------------------------------
{txt}
{com}. interact cohesion cohesion_population, cond(population) val(16.155);

Condition: population_ln=16.155
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
cohesion |{col 13} .0933551{col 24} .2209036{col 38} 0.423{col 47}0.673{col 58}-.3396079{col 70} .5263182
------------------------------------------------------------------------------
{txt}
{com}. interact cohesion cohesion_population, cond(population) val(17.468);

Condition: population_ln=17.468
Model    : regress

------------------------------------------------------------------------------
ctot_pct |{col 17}Coeff.{col 25}Std.Err.{col 41}z{col 47}P>|z|{col 59}[95% Conf. Interval]
---------+--------------------------------------------------------------------
cohesion |{col 13} -.804516{col 24} .3156318{col 38}-2.549{col 47}0.011{col 58}-1.423143{col 70} -.185889
------------------------------------------------------------------------------
{txt}
{com}. log close;
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/Christina/Dropbox/Work/Projects/2011/Weak States/analysis/replication package/WeakStates.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 7 Mar 2011, 09:28:16
{txt}{.-}
{smcl}
{txt}{sf}{ul off}